Totalistic cellular automata (CA) are an efficient tool for simulating numerous wave phenomena in discrete media. However, their inherent anisotropy often leads to a significant deviation of the model results from experimental data. Here we propose a computationally efficient isotropic CA with the standard Moore neighborhood. Our model exploits a single postulate: the information transfer in an isotropic medium occurs at constant rate. To fulfill this requirement we introduce in each cell a

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... l counter keeping track of the distance run by the wave from its source. This allows maintaining the wave velocity constant in all possible directions even in the presence of nonconductive local areas (obstacles) with complex spatial geometry. Then we illustrate the model on the problem of real-time building of cognitive maps used for navigation of a mobile robot. The isotropic property of the CA helps obtaining "smooth" trajectories and hence natural robot movement. The accuracy and flexibility of the approach are proved experimentally by driving the robot to a target avoiding collisions with obstacles.